Causal neural mechanisms of context-based object recognition
Objects can be recognized based on their intrinsic features, including shape, color, and texture. In daily life, however, such features are often not clearly visible, for example when objects appear in the periphery, in clutter, or at a distance. Interestingly, object recognition can still be highly...
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2021-08-01
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| Series: | eLife |
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| Online Access: | https://elifesciences.org/articles/69736 |
| _version_ | 1828168867301556224 |
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| author | Miles Wischnewski Marius V Peelen |
| author_facet | Miles Wischnewski Marius V Peelen |
| author_sort | Miles Wischnewski |
| collection | DOAJ |
| description | Objects can be recognized based on their intrinsic features, including shape, color, and texture. In daily life, however, such features are often not clearly visible, for example when objects appear in the periphery, in clutter, or at a distance. Interestingly, object recognition can still be highly accurate under these conditions when objects are seen within their typical scene context. What are the neural mechanisms of context-based object recognition? According to parallel processing accounts, context-based object recognition is supported by the parallel processing of object and scene information in separate pathways. Output of these pathways is then combined in downstream regions, leading to contextual benefits in object recognition. Alternatively, according to feedback accounts, context-based object recognition is supported by (direct or indirect) feedback from scene-selective to object-selective regions. Here, in three pre-registered transcranial magnetic stimulation (TMS) experiments, we tested a key prediction of the feedback hypothesis: that scene-selective cortex causally and selectively supports context-based object recognition before object-selective cortex does. Early visual cortex (EVC), object-selective lateral occipital cortex (LOC), and scene-selective occipital place area (OPA) were stimulated at three time points relative to stimulus onset while participants categorized degraded objects in scenes and intact objects in isolation, in different trials. Results confirmed our predictions: relative to isolated object recognition, context-based object recognition was selectively and causally supported by OPA at 160–200 ms after onset, followed by LOC at 260–300 ms after onset. These results indicate that context-based expectations facilitate object recognition by disambiguating object representations in the visual cortex. |
| first_indexed | 2024-04-12T02:41:51Z |
| format | Article |
| id | doaj.art-3891600d4b254c00a00784591166d4e5 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T02:41:51Z |
| publishDate | 2021-08-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-3891600d4b254c00a00784591166d4e52022-12-22T03:51:18ZengeLife Sciences Publications LtdeLife2050-084X2021-08-011010.7554/eLife.69736Causal neural mechanisms of context-based object recognitionMiles Wischnewski0Marius V Peelen1https://orcid.org/0000-0002-4026-7303Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands; Department of Biomedical Engineering, University of Minnesota, Minneapolis, United StatesDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, NetherlandsObjects can be recognized based on their intrinsic features, including shape, color, and texture. In daily life, however, such features are often not clearly visible, for example when objects appear in the periphery, in clutter, or at a distance. Interestingly, object recognition can still be highly accurate under these conditions when objects are seen within their typical scene context. What are the neural mechanisms of context-based object recognition? According to parallel processing accounts, context-based object recognition is supported by the parallel processing of object and scene information in separate pathways. Output of these pathways is then combined in downstream regions, leading to contextual benefits in object recognition. Alternatively, according to feedback accounts, context-based object recognition is supported by (direct or indirect) feedback from scene-selective to object-selective regions. Here, in three pre-registered transcranial magnetic stimulation (TMS) experiments, we tested a key prediction of the feedback hypothesis: that scene-selective cortex causally and selectively supports context-based object recognition before object-selective cortex does. Early visual cortex (EVC), object-selective lateral occipital cortex (LOC), and scene-selective occipital place area (OPA) were stimulated at three time points relative to stimulus onset while participants categorized degraded objects in scenes and intact objects in isolation, in different trials. Results confirmed our predictions: relative to isolated object recognition, context-based object recognition was selectively and causally supported by OPA at 160–200 ms after onset, followed by LOC at 260–300 ms after onset. These results indicate that context-based expectations facilitate object recognition by disambiguating object representations in the visual cortex.https://elifesciences.org/articles/69736objectsceneexpectationperceptioncategorization |
| spellingShingle | Miles Wischnewski Marius V Peelen Causal neural mechanisms of context-based object recognition eLife object scene expectation perception categorization |
| title | Causal neural mechanisms of context-based object recognition |
| title_full | Causal neural mechanisms of context-based object recognition |
| title_fullStr | Causal neural mechanisms of context-based object recognition |
| title_full_unstemmed | Causal neural mechanisms of context-based object recognition |
| title_short | Causal neural mechanisms of context-based object recognition |
| title_sort | causal neural mechanisms of context based object recognition |
| topic | object scene expectation perception categorization |
| url | https://elifesciences.org/articles/69736 |
| work_keys_str_mv | AT mileswischnewski causalneuralmechanismsofcontextbasedobjectrecognition AT mariusvpeelen causalneuralmechanismsofcontextbasedobjectrecognition |